{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Copyright 2019 NVIDIA Corporation. All Rights Reserved.\n",
    "#\n",
    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "# you may not use this file except in compliance with the License.\n",
    "# You may obtain a copy of the License at\n",
    "#\n",
    "#     http://www.apache.org/licenses/LICENSE-2.0\n",
    "#\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "# See the License for the specific language governing permissions and\n",
    "# limitations under the License.\n",
    "# =============================================================================="
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
    "\n",
    "# Torch-TensorRT Getting Started - EfficientNet-B0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview\n",
    "\n",
    "In the practice of developing machine learning models, there are few tools as approachable as PyTorch for developing and experimenting in designing machine learning models. The power of PyTorch comes from its deep integration into Python, its flexibility and its approach to automatic differentiation and execution (eager execution). However, when moving from research into production, the requirements change and we may no longer want that deep Python integration and we want optimization to get the best performance we can on our deployment platform. In PyTorch 1.0, TorchScript was introduced as a method to separate your PyTorch model from Python, make it portable and optimizable. TorchScript uses PyTorch's JIT compiler to transform your normal PyTorch code which gets interpreted by the Python interpreter to an intermediate representation (IR) which can have optimizations run on it and at runtime can get interpreted by the PyTorch JIT interpreter. For PyTorch this has opened up a whole new world of possibilities, including deployment in other languages like C++. It also introduces a structured graph based format that we can use to do down to the kernel level optimization of models for inference.\n",
    "\n",
    "When deploying on NVIDIA GPUs TensorRT, NVIDIA's Deep Learning Optimization SDK and Runtime is able to take models from any major framework and specifically tune them to perform better on specific target hardware in the NVIDIA family be it an A100, TITAN V, Jetson Xavier or NVIDIA's Deep Learning Accelerator. TensorRT performs a couple sets of optimizations to achieve this. TensorRT fuses layers and tensors in the model graph, it then uses a large kernel library to select implementations that perform best on the target GPU. TensorRT also has strong support for reduced operating precision execution which allows users to leverage the Tensor Cores on Volta and newer GPUs as well as reducing memory and computation footprints on device.\n",
    "\n",
    "Torch-TensorRT is a compiler that uses TensorRT to optimize TorchScript code, compiling standard TorchScript modules into ones that internally run with TensorRT optimizations. This enables you to continue to remain in the PyTorch ecosystem, using all the great features PyTorch has such as module composability, its flexible tensor implementation, data loaders and more. Torch-TensorRT is available to use with both PyTorch and LibTorch."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Learning objectives\n",
    "\n",
    "This notebook demonstrates the steps for compiling a TorchScript module with Torch-TensorRT on a pretrained EfficientNet network, and running it to test the speedup obtained.\n",
    "\n",
    "## Content\n",
    "1. [Requirements](#1)\n",
    "1. [EfficientNet Overview](#2)\n",
    "1. [Running the model without optimizations](#3)\n",
    "1. [Accelerating with Torch-TensorRT](#4)\n",
    "1. [Conclusion](#5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com\n",
      "Collecting timm==0.4.12\n",
      "  Downloading timm-0.4.12-py3-none-any.whl (376 kB)\n",
      "\u001b[K     |████████████████████████████████| 376 kB 11.9 MB/s eta 0:00:01\n",
      "\u001b[?25hRequirement already satisfied: torch>=1.4 in /opt/conda/lib/python3.8/site-packages (from timm==0.4.12) (1.11.0a0+bfe5ad2)\n",
      "Requirement already satisfied: torchvision in /opt/conda/lib/python3.8/site-packages (from timm==0.4.12) (0.12.0a0)\n",
      "Requirement already satisfied: typing_extensions in /opt/conda/lib/python3.8/site-packages (from torch>=1.4->timm==0.4.12) (4.0.1)\n",
      "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /opt/conda/lib/python3.8/site-packages (from torchvision->timm==0.4.12) (8.2.0)\n",
      "Requirement already satisfied: numpy in /opt/conda/lib/python3.8/site-packages (from torchvision->timm==0.4.12) (1.22.0)\n",
      "Installing collected packages: timm\n",
      "Successfully installed timm-0.4.12\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n",
      "Fri Feb  4 21:29:36 2022       \n",
      "+-----------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 510.39.01    Driver Version: 510.39.01    CUDA Version: 11.6     |\n",
      "|-------------------------------+----------------------+----------------------+\n",
      "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                               |                      |               MIG M. |\n",
      "|===============================+======================+======================|\n",
      "|   0  NVIDIA GeForce ...  On   | 00000000:65:00.0 Off |                  N/A |\n",
      "| 30%   28C    P8    11W / 350W |      0MiB / 24576MiB |      0%      Default |\n",
      "|                               |                      |                  N/A |\n",
      "+-------------------------------+----------------------+----------------------+\n",
      "                                                                               \n",
      "+-----------------------------------------------------------------------------+\n",
      "| Processes:                                                                  |\n",
      "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
      "|        ID   ID                                                   Usage      |\n",
      "|=============================================================================|\n",
      "|  No running processes found                                                 |\n",
      "+-----------------------------------------------------------------------------+\n"
     ]
    }
   ],
   "source": [
    "!pip install timm==0.4.12\n",
    "!nvidia-smi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"1\"></a>\n",
    "## 1. Requirements\n",
    "\n",
    "NVIDIA's NGC provides PyTorch Docker Container which contains PyTorch and Torch-TensorRT. We can make use of [latest pytorch](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch) container to run this notebook.\n",
    "\n",
    "Otherwise, you can follow the steps in `notebooks/README` to prepare a Docker container yourself, within which you can run this demo notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"2\"></a>\n",
    "## 2. EfficientNet Overview\n",
    "\n",
    "\n",
    "PyTorch has a model repository called `timm`, which is a source for high quality implementations of computer vision models. We can get our EfficientNet model from there pretrained on ImageNet.\n",
    "\n",
    "### Model Description\n",
    "\n",
    "This model is based on the [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946) paper.\n",
    "\n",
    "<img src=\"https://1.bp.blogspot.com/-Cdtb97FtgdA/XO3BHsB7oEI/AAAAAAAAEKE/bmtkonwgs8cmWyI5esVo8wJPnhPLQ5bGQCLcBGAs/s1600/image4.png\" alt=\"alt\" width=\"100%\"/>\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"3\"></a>\n",
    "## 3. Running the model without optimizations\n",
    "\n",
    "\n",
    "PyTorch has a model repository called `timm`, which is a source for high quality implementations of computer vision models. We can get our EfficientNet model from there pretrained on ImageNet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch_tensorrt\n",
    "import timm\n",
    "import time\n",
    "import numpy as np\n",
    "import torch.backends.cudnn as cudnn\n",
    "from timm.data import resolve_data_config\n",
    "from timm.data.transforms_factory import create_transform\n",
    "import json \n",
    "\n",
    "efficientnet_b0_model = timm.create_model('efficientnet_b0',pretrained=True)\n",
    "model = efficientnet_b0_model.eval().to(\"cuda\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With our model loaded, let's proceed to downloading some images!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2022-02-04 21:30:07--  https://d17fnq9dkz9hgj.cloudfront.net/breed-uploads/2018/08/siberian-husky-detail.jpg?bust=1535566590&width=630\n",
      "Resolving d17fnq9dkz9hgj.cloudfront.net (d17fnq9dkz9hgj.cloudfront.net)... 18.65.227.127, 18.65.227.37, 18.65.227.99, ...\n",
      "Connecting to d17fnq9dkz9hgj.cloudfront.net (d17fnq9dkz9hgj.cloudfront.net)|18.65.227.127|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 24112 (24K) [image/jpeg]\n",
      "Saving to: ‘./data/img0.JPG’\n",
      "\n",
      "./data/img0.JPG     100%[===================>]  23.55K  --.-KB/s    in 0.004s  \n",
      "\n",
      "2022-02-04 21:30:07 (6.40 MB/s) - ‘./data/img0.JPG’ saved [24112/24112]\n",
      "\n",
      "--2022-02-04 21:30:07--  https://www.hakaimagazine.com/wp-content/uploads/header-gulf-birds.jpg\n",
      "Resolving www.hakaimagazine.com (www.hakaimagazine.com)... 164.92.73.117\n",
      "Connecting to www.hakaimagazine.com (www.hakaimagazine.com)|164.92.73.117|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 452718 (442K) [image/jpeg]\n",
      "Saving to: ‘./data/img1.JPG’\n",
      "\n",
      "./data/img1.JPG     100%[===================>] 442.11K  --.-KB/s    in 0.06s   \n",
      "\n",
      "2022-02-04 21:30:07 (6.83 MB/s) - ‘./data/img1.JPG’ saved [452718/452718]\n",
      "\n",
      "--2022-02-04 21:30:08--  https://www.artis.nl/media/filer_public_thumbnails/filer_public/00/f1/00f1b6db-fbed-4fef-9ab0-84e944ff11f8/chimpansee_amber_r_1920x1080.jpg__1920x1080_q85_subject_location-923%2C365_subsampling-2.jpg\n",
      "Resolving www.artis.nl (www.artis.nl)... 94.75.225.20\n",
      "Connecting to www.artis.nl (www.artis.nl)|94.75.225.20|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 361413 (353K) [image/jpeg]\n",
      "Saving to: ‘./data/img2.JPG’\n",
      "\n",
      "./data/img2.JPG     100%[===================>] 352.94K   246KB/s    in 1.4s    \n",
      "\n",
      "2022-02-04 21:30:10 (246 KB/s) - ‘./data/img2.JPG’ saved [361413/361413]\n",
      "\n",
      "--2022-02-04 21:30:10--  https://www.familyhandyman.com/wp-content/uploads/2018/09/How-to-Avoid-Snakes-Slithering-Up-Your-Toilet-shutterstock_780480850.jpg\n",
      "Resolving www.familyhandyman.com (www.familyhandyman.com)... 104.18.202.107, 104.18.201.107, 2606:4700::6812:ca6b, ...\n",
      "Connecting to www.familyhandyman.com (www.familyhandyman.com)|104.18.202.107|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 90994 (89K) [image/jpeg]\n",
      "Saving to: ‘./data/img3.JPG’\n",
      "\n",
      "./data/img3.JPG     100%[===================>]  88.86K  --.-KB/s    in 0.006s  \n",
      "\n",
      "2022-02-04 21:30:10 (14.4 MB/s) - ‘./data/img3.JPG’ saved [90994/90994]\n",
      "\n",
      "--2022-02-04 21:30:11--  https://s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json\n",
      "Resolving s3.amazonaws.com (s3.amazonaws.com)... 52.216.133.45\n",
      "Connecting to s3.amazonaws.com (s3.amazonaws.com)|52.216.133.45|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 35363 (35K) [application/octet-stream]\n",
      "Saving to: ‘./data/imagenet_class_index.json’\n",
      "\n",
      "./data/imagenet_cla 100%[===================>]  34.53K  --.-KB/s    in 0.07s   \n",
      "\n",
      "2022-02-04 21:30:11 (474 KB/s) - ‘./data/imagenet_class_index.json’ saved [35363/35363]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!mkdir -p ./data\n",
    "!wget  -O ./data/img0.JPG \"https://d17fnq9dkz9hgj.cloudfront.net/breed-uploads/2018/08/siberian-husky-detail.jpg?bust=1535566590&width=630\"\n",
    "!wget  -O ./data/img1.JPG \"https://www.hakaimagazine.com/wp-content/uploads/header-gulf-birds.jpg\"\n",
    "!wget  -O ./data/img2.JPG \"https://www.artis.nl/media/filer_public_thumbnails/filer_public/00/f1/00f1b6db-fbed-4fef-9ab0-84e944ff11f8/chimpansee_amber_r_1920x1080.jpg__1920x1080_q85_subject_location-923%2C365_subsampling-2.jpg\"\n",
    "!wget  -O ./data/img3.JPG \"https://www.familyhandyman.com/wp-content/uploads/2018/09/How-to-Avoid-Snakes-Slithering-Up-Your-Toilet-shutterstock_780480850.jpg\"\n",
    "\n",
    "!wget  -O ./data/imagenet_class_index.json \"https://s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All pre-trained models expect input images normalized in the same way,\n",
    "i.e. mini-batches of 3-channel RGB images of shape `(3 x H x W)`, where `H` and `W` are expected to be at least `224`.\n",
    "The images have to be loaded in to a range of `[0, 1]` and then normalized using `mean = [0.485, 0.456, 0.406]`\n",
    "and `std = [0.229, 0.224, 0.225]`.\n",
    "\n",
    "Here's a sample execution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from PIL import Image\n",
    "from torchvision import transforms\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, axes = plt.subplots(nrows=2, ncols=2)\n",
    "\n",
    "for i in range(4):\n",
    "    img_path = './data/img%d.JPG'%i\n",
    "    img = Image.open(img_path)\n",
    "    preprocess = transforms.Compose([\n",
    "        transforms.Resize(256),\n",
    "        transforms.CenterCrop(224),\n",
    "        transforms.ToTensor(),\n",
    "        transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),\n",
    "    ])\n",
    "    input_tensor = preprocess(img)      \n",
    "    plt.subplot(2,2,i+1)\n",
    "    plt.imshow(img)\n",
    "    plt.axis('off')\n",
    "\n",
    "# loading labels\n",
    "with open(\"./data/imagenet_class_index.json\") as json_file: \n",
    "    d = json.load(json_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Throughout this tutorial, we will be making use of some utility functions; `efficientnet_preprocess` for preprocessing input images, `predict` to use the model for prediction and `benchmark` to benchmark the inference. You do not need to understand/go through these utilities to make use of Torch TensorRT, but are welecomed to do so if you choose."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "cudnn.benchmark = True\n",
    "\n",
    "def efficientnet_preprocess():\n",
    "    config = resolve_data_config({}, model=model)\n",
    "    transform = create_transform(**config)\n",
    "    return transform\n",
    "\n",
    "# decode the results into ([predicted class, description], probability)\n",
    "def predict(img_path, model):\n",
    "    img = Image.open(img_path)\n",
    "    preprocess = efficientnet_preprocess()\n",
    "    input_tensor = preprocess(img)\n",
    "    input_batch = input_tensor.unsqueeze(0) # create a mini-batch as expected by the model\n",
    "    \n",
    "    # move the input and model to GPU for speed if available\n",
    "    if torch.cuda.is_available():\n",
    "        input_batch = input_batch.to('cuda')\n",
    "        model.to('cuda')\n",
    "\n",
    "    with torch.no_grad():\n",
    "        output = model(input_batch)\n",
    "        # Tensor of shape 1000, with confidence scores over Imagenet's 1000 classes\n",
    "        sm_output = torch.nn.functional.softmax(output[0], dim=0)\n",
    "        \n",
    "    ind = torch.argmax(sm_output)\n",
    "    return d[str(ind.item())], sm_output[ind] #([predicted class, description], probability)\n",
    "\n",
    "def benchmark(model, input_shape=(1024, 1, 224, 224), dtype='fp32', nwarmup=50, nruns=10000):\n",
    "    input_data = torch.randn(input_shape)\n",
    "    input_data = input_data.to(\"cuda\")\n",
    "    if dtype=='fp16':\n",
    "        input_data = input_data.half()\n",
    "        \n",
    "    print(\"Warm up ...\")\n",
    "    with torch.no_grad():\n",
    "        for _ in range(nwarmup):\n",
    "            features = model(input_data)\n",
    "    torch.cuda.synchronize()\n",
    "    print(\"Start timing ...\")\n",
    "    timings = []\n",
    "    with torch.no_grad():\n",
    "        for i in range(1, nruns+1):\n",
    "            start_time = time.time()\n",
    "            features = model(input_data)\n",
    "            torch.cuda.synchronize()\n",
    "            end_time = time.time()\n",
    "            timings.append(end_time - start_time)\n",
    "            if i%10==0:\n",
    "                print('Iteration %d/%d, avg batch time %.2f ms'%(i, nruns, np.mean(timings)*1000))\n",
    "\n",
    "    print(\"Input shape:\", input_data.size())\n",
    "    print(\"Output features size:\", features.size())\n",
    "    print('Average throughput: %.2f images/second'%(input_shape[0]/np.mean(timings)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the model downloaded and the util functions written, let's just quickly see some predictions, and benchmark the model in its current un-optimized state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.8/site-packages/torchvision/transforms/transforms.py:321: UserWarning: Argument interpolation should be of type InterpolationMode instead of int. Please, use InterpolationMode enum.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./data/img0.JPG - Predicted: ['n02109961', 'Eskimo_dog'], Probablility: 0.3987298309803009\n",
      "./data/img1.JPG - Predicted: ['n01537544', 'indigo_bunting'], Probablility: 0.23344755172729492\n",
      "./data/img2.JPG - Predicted: ['n02481823', 'chimpanzee'], Probablility: 0.9695423245429993\n",
      "./data/img3.JPG - Predicted: ['n01739381', 'vine_snake'], Probablility: 0.227739155292511\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(4):\n",
    "    img_path = './data/img%d.JPG'%i\n",
    "    img = Image.open(img_path)\n",
    "    \n",
    "    pred, prob = predict(img_path, efficientnet_b0_model)\n",
    "    print('{} - Predicted: {}, Probablility: {}'.format(img_path, pred, prob))\n",
    "\n",
    "    plt.subplot(2,2,i+1)\n",
    "    plt.imshow(img);\n",
    "    plt.axis('off');\n",
    "    plt.title(pred[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warm up ...\n",
      "Start timing ...\n",
      "Iteration 10/100, avg batch time 37.62 ms\n",
      "Iteration 20/100, avg batch time 37.66 ms\n",
      "Iteration 30/100, avg batch time 37.65 ms\n",
      "Iteration 40/100, avg batch time 37.66 ms\n",
      "Iteration 50/100, avg batch time 37.70 ms\n",
      "Iteration 60/100, avg batch time 37.70 ms\n",
      "Iteration 70/100, avg batch time 37.70 ms\n",
      "Iteration 80/100, avg batch time 37.71 ms\n",
      "Iteration 90/100, avg batch time 37.72 ms\n",
      "Iteration 100/100, avg batch time 37.72 ms\n",
      "Input shape: torch.Size([128, 3, 224, 224])\n",
      "Output features size: torch.Size([128, 1000])\n",
      "Average throughput: 3393.46 images/second\n"
     ]
    }
   ],
   "source": [
    "# Model benchmark without Torch-TensorRT\n",
    "benchmark(model, input_shape=(128, 3, 224, 224), nruns=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"4\"></a>\n",
    "## 4. Accelerating with Torch-TensorRT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Onwards to the next step, accelerating with Torch TensorRT. In these examples we showcase the results for FP32 (single precision) and FP16 (half precision). We do not demonstrat specific tuning, just showcase the simplicity of usage. If you want to learn more about the possible customizations, visit our [documentation](https://nvidia.github.io/Torch-TensorRT/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FP32 (single precision)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n"
     ]
    }
   ],
   "source": [
    "# The compiled module will have precision as specified by \"op_precision\".\n",
    "# Here, it will have FP32 precision.\n",
    "trt_model_fp32 = torch_tensorrt.compile(model, inputs = [torch_tensorrt.Input((128, 3, 224, 224), dtype=torch.float32)],\n",
    "    enabled_precisions = torch.float32, # Run with FP32\n",
    "    workspace_size = 1 << 22\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warm up ...\n",
      "Start timing ...\n",
      "Iteration 10/100, avg batch time 27.86 ms\n",
      "Iteration 20/100, avg batch time 27.71 ms\n",
      "Iteration 30/100, avg batch time 27.99 ms\n",
      "Iteration 40/100, avg batch time 27.95 ms\n",
      "Iteration 50/100, avg batch time 27.89 ms\n",
      "Iteration 60/100, avg batch time 27.85 ms\n",
      "Iteration 70/100, avg batch time 28.00 ms\n",
      "Iteration 80/100, avg batch time 27.97 ms\n",
      "Iteration 90/100, avg batch time 27.95 ms\n",
      "Iteration 100/100, avg batch time 27.92 ms\n",
      "Input shape: torch.Size([128, 3, 224, 224])\n",
      "Output features size: torch.Size([128, 1000])\n",
      "Average throughput: 4584.06 images/second\n"
     ]
    }
   ],
   "source": [
    "# Obtain the average time taken by a batch of input\n",
    "benchmark(trt_model_fp32, input_shape=(128, 3, 224, 224), nruns=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FP16 (half precision)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: [Torch-TensorRT] - For input x.1, found user specified input dtype as Float16, however when inspecting the graph, the input type expected was inferred to be Float\n",
      "The compiler is going to use the user setting Float16\n",
      "This conflict may cause an error at runtime due to partial compilation being enabled and therefore\n",
      "compatibility with PyTorch's data type convention is required.\n",
      "If you do indeed see errors at runtime either:\n",
      "- Remove the dtype spec for x.1\n",
      "- Disable partial compilation by setting require_full_compilation to True\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT] - Mean converter disregards dtype\n",
      "WARNING: [Torch-TensorRT TorchScript Conversion Context] - Tensor DataType is determined at build time for tensors not marked as input or output.\n",
      "WARNING: [Torch-TensorRT TorchScript Conversion Context] - Tensor DataType is determined at build time for tensors not marked as input or output.\n"
     ]
    }
   ],
   "source": [
    "# The compiled module will have precision as specified by \"op_precision\".\n",
    "# Here, it will have FP16 precision.\n",
    "trt_model_fp16 = torch_tensorrt.compile(model, inputs = [torch_tensorrt.Input((128, 3, 224, 224), dtype=torch.half)],\n",
    "    enabled_precisions = {torch.half}, # Run with FP32\n",
    "    workspace_size = 1 << 22\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warm up ...\n",
      "Start timing ...\n",
      "Iteration 10/100, avg batch time 12.05 ms\n",
      "Iteration 20/100, avg batch time 12.56 ms\n",
      "Iteration 30/100, avg batch time 12.39 ms\n",
      "Iteration 40/100, avg batch time 12.34 ms\n",
      "Iteration 50/100, avg batch time 12.33 ms\n",
      "Iteration 60/100, avg batch time 12.32 ms\n",
      "Iteration 70/100, avg batch time 12.30 ms\n",
      "Iteration 80/100, avg batch time 12.28 ms\n",
      "Iteration 90/100, avg batch time 12.35 ms\n",
      "Iteration 100/100, avg batch time 12.35 ms\n",
      "Input shape: torch.Size([128, 3, 224, 224])\n",
      "Output features size: torch.Size([128, 1000])\n",
      "Average throughput: 10362.23 images/second\n"
     ]
    }
   ],
   "source": [
    "# Obtain the average time taken by a batch of input\n",
    "benchmark(trt_model_fp16, input_shape=(128, 3, 224, 224), dtype='fp16', nruns=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id=\"5\"></a>\n",
    "## 5. Conclusion\n",
    "\n",
    "In this notebook, we have walked through the complete process of compiling TorchScript models with Torch-TensorRT for EfficientNet-B0 model and test the performance impact of the optimization. With Torch-TensorRT, we observe a speedup of **1.35x** with FP32, and **3.13x** with FP16 on an NVIDIA 3090 GPU. These acceleration numbers will vary from GPU to GPU(as well as implementation to implementation based on the ops used) and we encorage you to try out latest generation of Data center compute cards for maximum acceleration.\n",
    "\n",
    "### What's next\n",
    "Now it's time to try Torch-TensorRT on your own model. If you run into any issues, you can fill them at https://github.com/NVIDIA/Torch-TensorRT. Your involvement will help future development of Torch-TensorRT.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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